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      Proof-of-concept for an automatable mortality prediction scoring in hospitalised older adults

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          Abstract

          Introduction

          It is challenging to prognosticate hospitalised older adults. Delayed recognition of end-of-life leads to failure in delivering appropriate palliative care and increases healthcare utilisation. Most mortality prediction tools specific for older adults require additional manual input, resulting in poor uptake. By leveraging on electronic health records, we aim to create an automatable mortality prediction tool for hospitalised older adults.

          Methods

          We retrospectively reviewed electronic records of general medicine patients ≥75 years at a tertiary hospital between April–September 2021. Demographics, comorbidities, ICD-codes, age-adjusted Charlson Comorbidity Index (CCI), Hospital Frailty Risk Score, mortality and resource utilization were collected. We defined early deaths, late deaths and survivors as patients who died within 30 days, 1 year, and lived beyond 1 year of admission, respectively. Multivariate logistic regression analyses were adjusted for age, gender, race, frailty, and CCI. The final prediction model was created using a stepwise logistic regression.

          Results

          Of 1,224 patients, 168 (13.7%) died early and 370 (30.2%) died late. From adjusted multivariate regression, risk of early death was significantly associated with ≥85 years, intermediate or high frail risk, CCI > 6, cardiovascular risk factors, AMI and pneumonia. For late death, risk factors included ≥85 years, intermediate frail risk, CCI >6, delirium, diabetes, AMI and pneumonia. Our mortality prediction tool which scores 1 point each for age, pneumonia and AMI had an AUC of 0.752 for early death and 0.691 for late death.

          Conclusion

          Our mortality prediction model is a proof-of-concept demonstrating the potential for automated medical alerts to guide physicians towards personalised care for hospitalised older adults.

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          Most cited references39

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          Frailty in Older Adults: Evidence for a Phenotype

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            A global clinical measure of fitness and frailty in elderly people.

            There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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              APACHE II: a severity of disease classification system.

              This paper presents the form and validation results of APACHE II, a severity of disease classification system. APACHE II uses a point score based upon initial values of 12 routine physiologic measurements, age, and previous health status to provide a general measure of severity of disease. An increasing score (range 0 to 71) was closely correlated with the subsequent risk of hospital death for 5815 intensive care admissions from 13 hospitals. This relationship was also found for many common diseases. When APACHE II scores are combined with an accurate description of disease, they can prognostically stratify acutely ill patients and assist investigators comparing the success of new or differing forms of therapy. This scoring index can be used to evaluate the use of hospital resources and compare the efficacy of intensive care in different hospitals or over time.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/2049826/overviewRole: Role:
                URI : https://loop.frontiersin.org/people/1784486/overviewRole: Role:
                Role: Role:
                URI : https://loop.frontiersin.org/people/1448945/overviewRole: Role: Role:
                URI : https://loop.frontiersin.org/people/919640/overviewRole: Role: Role: Role:
                Journal
                Front Med (Lausanne)
                Front Med (Lausanne)
                Front. Med.
                Frontiers in Medicine
                Frontiers Media S.A.
                2296-858X
                23 May 2024
                2024
                : 11
                : 1329107
                Affiliations
                [1] 1Division of Geriatric Medicine, Department of Medicine, National University Health System , Singapore, Singapore
                [2] 2Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore , Singapore, Singapore
                [3] 3Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore , Singapore, Singapore
                Author notes

                Edited by: Tzvi Dwolatzky, Technion Israel Institute of Technology, Israel

                Reviewed by: Honoria Ocagli, University of Padua, Italy

                Esra Ates Bulut, Ministry of Health (Turkey), Türkiye

                *Correspondence: Natalie M. W. Ling, natalie_ling@ 123456nuhs.edu.sg
                Article
                10.3389/fmed.2024.1329107
                11153690
                38846139
                a464ea73-a430-4e8c-9034-2fec28d17d9d
                Copyright © 2024 Ho, Ling, Anbarasan, Chan and Merchant.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 October 2023
                : 24 April 2024
                Page count
                Figures: 0, Tables: 3, Equations: 0, References: 41, Pages: 7, Words: 5847
                Funding
                The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
                Categories
                Medicine
                Original Research
                Custom metadata
                Geriatric Medicine

                older adults,hospitalisation,survivorship,mortality,predictive tool

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